ry/tfjs-core

WebGL-accelerated ML // linear algebra // automatic differentiation for JavaScript.

TensorFlow.js Core API

NOTE: Building on the momentum of deeplearn.js, we have joined the TensorFlow family and we are starting a new ecosystem of libraries and tools for Machine Learning in Javascript, called TensorFlow.js. This repo moved from PAIR-code/deeplearnjs to tensorflow/tfjs-core.

A part of the TensorFlow.js ecosystem, this repo hosts @tensorflow/tfjs-core, the TensorFlow.js Core API, which provides low-level, hardware-accelerated linear algebra operations and an eager API for automatic differentiation.

Check out js.tensorflow.org for more information about the library, tutorials and API docs.

To keep track of issues, we use the tensorflow/tfjs Github repo.

Importing

You can install TensorFlow.js via yarn or npm. We recommend using the @tensorflow/tfjs npm package, which gives you both this Core API and the higher-level Layers API:

import * as tf from '@tensorflow/tfjs';
// You have the Core API: tf.matMul(), tf.softmax(), ...
// You also have Layers API: tf.model(), tf.layers.dense(), ...

On the other hand, if you care about the bundle size and you do not use the Layers API, you can import only the Core API:

import * as tfc from '@tensorflow/tfjs-core';
// You have the Core API: tfc.matMul(), tfc.softmax(), ...
// No Layers API.

For info about development, check out DEVELOPMENT.md.

For more information

• TensorFlow.js API documentation
• TensorFlow.js Tutorials

Thanks BrowserStack for providing testing support.